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    Results for "advanced statistics"

    • K

      Kennesaw State University

      Six Sigma Advanced Analyze Phase

      Skills you'll gain: Statistical Hypothesis Testing, Six Sigma Methodology, Lean Six Sigma, Process Improvement, Process Analysis, Statistical Methods, Statistical Analysis, Statistics, Data Analysis, Analytical Skills, Variance Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      950 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of California, Santa Cruz

      C for Everyone: Structured Programming

      Skills you'll gain: C (Programming Language), Debugging, C++ (Programming Language), Data Structures, Computer Programming, Command-Line Interface, Algorithms, Integrated Development Environments, Program Development, File Systems

      4.6
      Rating, 4.6 out of 5 stars
      ·
      765 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Supervised Machine Learning: Classification

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
      ·
      407 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Bayesian Network, Bayesian Statistics, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      488 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Geneva

      Ecosystem Services: a Method for Sustainable Development

      Skills you'll gain: Geographic Information Systems, Environment, Natural Resource Management, Spatial Analysis, Environmental Science, Environmental Policy, Socioeconomics, Sustainability Reporting, Economics, Governance, Stakeholder Engagement, Ethical Standards And Conduct

      4.8
      Rating, 4.8 out of 5 stars
      ·
      713 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Imperial College London

      Global Disease Masterclass

      Skills you'll gain: Infectious Diseases, Epidemiology, Public Health and Disease Prevention, Public Health, Health Disparities, Cardiology, Chronic Diseases, Microbiology, Community Health, Health Systems, Health Policy, Socioeconomics, Preventative Care, Health Care, Health Assessment, Biostatistics, Data Analysis, Policy Analysis, Trend Analysis, Medical Science and Research

      4.8
      Rating, 4.8 out of 5 stars
      ·
      315 reviews

      Beginner · Specialization · 1 - 3 Months

    • B

      Board Infinity

      Fundamentals of Java Programming

      Skills you'll gain: Eclipse (Software), Object Oriented Programming (OOP), Java Programming, Object Oriented Design, Java, Integrated Development Environments, Development Environment, Computer Programming, Programming Principles, Virtual Machines

      4.4
      Rating, 4.4 out of 5 stars
      ·
      496 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Achieving Advanced Insights with BigQuery

      Skills you'll gain: SQL, Big Data, Google Cloud Platform, Data Access, Database Architecture and Administration, Performance Tuning, Jupyter, Data Warehousing, Data Security, Data Science, Data Structures

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Cape Town

      Julia Scientific Programming

      Skills you'll gain: Box Plots, Jupyter, Statistical Analysis, Data Visualization, Scientific Visualization, Exploratory Data Analysis, Descriptive Statistics, Data Manipulation, Data Science, Other Programming Languages, Data Import/Export, Computer Programming, Mathematical Modeling, Package and Software Management

      4.4
      Rating, 4.4 out of 5 stars
      ·
      433 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      SAS

      Statistical Thinking for Industrial Problem Solving, presented by JMP

      Skills you'll gain: Exploratory Data Analysis, Data Compilation, Correlation Analysis, Data Collection, Statistical Inference, Statistical Methods, Statistical Modeling, Predictive Modeling, Data Analysis, Data-Driven Decision-Making, Regression Analysis, Statistical Analysis, Probability & Statistics, Statistical Visualization

      4.9
      Rating, 4.9 out of 5 stars
      ·
      92 reviews

      Beginner · Course · 1 - 3 Months

    • N

      New York Institute of Finance

      Operational Risk Management: Frameworks & Strategies

      Skills you'll gain: Operational Risk, Risk Management Framework, Risk Management, Business Risk Management, Enterprise Risk Management (ERM), Risk Appetite, Risk Control, Governance, Risk Analysis, Key Performance Indicators (KPIs), Business Process, Regulatory Requirements, Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      351 reviews

      Beginner · Course · 1 - 3 Months

    • P

      Palo Alto Networks

      Palo Alto Networks Cybersecurity Foundation

      Skills you'll gain: Cybersecurity, Zero Trust Network Access, Cyber Threat Intelligence, Malware Protection, Network Security, Firewall, Threat Detection, Cloud Security, Endpoint Security, Security Controls, Enterprise Security, Software As A Service, Cloud Computing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      488 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    advanced linear models for data science 2: statistical linear models
    1…414243…262

    In summary, here are 10 of our most popular advanced statistics courses

    • Six Sigma Advanced Analyze Phase: Kennesaw State University
    • C for Everyone: Structured Programming: University of California, Santa Cruz
    • Supervised Machine Learning: Classification: IBM
    • Probabilistic Graphical Models 2: Inference: Stanford University
    • Ecosystem Services: a Method for Sustainable Development: University of Geneva
    • Global Disease Masterclass: Imperial College London
    • Fundamentals of Java Programming: Board Infinity
    • Achieving Advanced Insights with BigQuery: Google Cloud
    • Julia Scientific Programming: University of Cape Town
    • Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS

    Frequently Asked Questions about Advanced Statistics

    Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

    These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.‎

    Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

    Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.‎

    Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.‎

    You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.‎

    People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.‎

    If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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